@__forward_call_369(%arg0: tensor<16x224x224x3xf32> {tf._user_specified_name = "inputs"}, %arg1: tensor<*x!tf_type.resource>, %arg2: tensor<*x!tf_type.resource>, %arg3: tensor<*x!tf_type.resource>, %arg4: tensor<*x!tf_type.resource>) -> (tensor<?x?xf32>, tensor<*xf32>, tensor<?x16384xf32>, tensor<16x112x112x?xf32>, tensor<16x224x224x3xf32>, tensor<*xf32>) attributes {tf.entry_function = {control_outputs = "", inputs = "inputs_0,conv1_conv2d_readvariableop_resource,conv1_biasadd_readvariableop_resource...

    RunOptions run_options;

    Tensor input_a = CreateInputTensor(shape, 0);
    Tensor input_b = CreateInputTensor(shape, shape.num_elements());
    Tensor input_c = CreateInputTensor(shape, 2 * shape.num_elements());
    TF_RETURN_IF_ERROR(session->Run(
        run_options,
        {std::make_pair("a", input_a), std::make_pair("b", input_b),
         std::make_pair("c", input_c)},
        {"m"}, {}, &golden_output_tensors, nullptr));

           const std::vector<T>& expected_output_values) {
    ClientSession session(scope_);

    DCHECK_EQ(input_values.size(), inputs_.size());
    ClientSession::FeedType feeds;
    for (int i = 0; i < inputs_.size(); ++i) {
      feeds.emplace(inputs_[i], input_values[i]);
    }

    std::vector<Tensor> out_tensors;
    TF_ASSERT_OK(session.Run(feeds, outputs_, &out_tensors));

        readingList.add(toKatakana(text));
        return readingList;
    }

    protected String toKatakana(final String inputStr) throws IOException {
        final StringBuilder kanaBuf = new StringBuilder();

        final Reader rd = new StringReader(inputStr);
        try (TokenStream stream = createTokenStream(rd)) {
            if (stream == null) {
                throw new IOException("Invalid tokenizer.");

  %result:4 = tf_device.replicate([%arg0, %arg1] as %input0: tensor<*xf32>) {n = 2 : i32} {
    tf_device.return %input0, %arg2 : tensor<*xf32>, tensor<*xi32>
  }
  func.return

// CHECK:      tf_device.replicate
// CHECK-SAME: ([%[[ARG_0]], %[[ARG_1]]] as %[[INPUT_0:[a-z0-9]*]]: tensor<*xf32>)
// CHECK-SAME: n = 2
// CHECK-NEXT:   tf_device.return %[[INPUT_0]], %[[ARG_2]]
}

// -----

module {
func.func @main(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>, %arg2: tensor<1xf32>, %arg3: tensor<1xf32>) -> tensor<2x1xf32> attributes {tf.entry_function = {inputs = "input0,input1,input2,input3", outputs = "output"}} {
  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>

// RUN: tf-opt -split-input-file -verify-diagnostics -tf-tpu-annotate-dynamic-shape-inputs %s | FileCheck %s

// Test that annotate the inputs of the cluster func to be dynamic shaped.

module attributes {tf.devices = ["/job:worker/replica:0/task:0/device:CPU:0", "/job:worker/replica:0/task:0/device:TPU_SYSTEM:0", "/job:worker/replica:0/task:0/device:TPU:0"]} {
   func.func @main(
      %arg0: tensor<2048xi64> {tf.device = "/job:localhost/replica:0/task:0/device:CPU:0"},

        private final ModelType<T> type;
        private final List<ModelReference<?>> inputs;

        private UnmanagedElementCreationAction(ModelRuleDescriptor descriptor, ModelReference<?> subject, List<ModelReference<?>> inputs, ModelType<T> type) {
            this.subject = subject;
            this.inputs = inputs;
            this.descriptor = descriptor;
            this.type = type;
        }

        @Override

            this.inputs = inputs;
            this.ruleSourceType = ruleSourceType;
            this.ruleExtractor = ruleExtractor;
        }

        @Override
        public ModelReference<?> getSubject() {
            return targetReference;
        }

        @Override
        public List<? extends ModelReference<?>> getInputs() {
            return inputs;
        }

        @Override

          absl::StrCat("tensor parsing error: ", alias));
    }

    inputs.emplace_back(feed_name, tensor);
  }

  if (!request_inputs.empty() &&
      seen_request_inputs.size() != request_inputs.size()) {
    return absl::InvalidArgumentError(absl::StrCat(
        "Inputs contains invalid name. Used request inputs: ",
        absl::StrJoin(seen_request_inputs, ","),